"COMPUTER VISION" by Yoshiaki Shirai, page 169, FIG. 8.12, issued by Shokodo Co., Ltd. on Apr. 30, 1980 discloses a known system used in this kind of linearity discrimination method. FIGS. 1A to 1D show conventional linearity discriminating systems, in which the general construction of the visual information processing systems are respectively illustrated. The optimum system can be selected from among those shown in FIGS. 1A to 1D in accordance with the purpose of a particular use.
FIG. 1A shows a system for analyzing bubble chamber photography. A flying spot scanner (FSS) 101 is controlled by a dedicated control section 103 and an image feature is discriminated by a computer 102. FIG. 1B shows a system which may be used to detect scratches on a printed circuit board, or to recognize a water supply port and a water exhaust port or a pump system, or the like, and which comprises only a dedicated apparatus 104. FIG. 1C shows a system in which flexible control that cannot be performed solely by dedicated apparatuses 105 and 106 is executed by a microcomputer 107. This system may be used for wire bonding work on IC devices. The system shown in FIG. 1D is suitable for use in a case where an object is observed by TV cameras 108 to 111 so that tasks can be executed on the basis of the observed object. Since dedicated apparatuses 112 and 113 need not operate while the relevant work is being conducted, the signals from a plurality of TV cameras can be processed by a single dedicated apparatus. The system of FIG. 1D is also used to execute wire-bonding work on IC devices or transistors. Reference numeral 114 denotes a computer.
Returning to the above-mentioned publication, reference will be made to the portion from page 36, which is directly concerned with the subject matter of the present patent application. FIGS. 2A to 2C correspond to FIG. 2.24 in the publication. FIG. 2A shows a train of points which can be obtained from the input image. It is to be noted that the direction of the train of points is defined by the direction of a line connecting that point and a point which precedes that point by k points. Assuming that the distance from point A as measured along the train of points is s, the direction .psi.(s) at each point in the straight line portion is almost constant, and the gradient of .psi.(s) in the arc-like portion is constant (FIG. 2B). Assuming that the curvature .phi.(s) at each point in the train of points is defined by the difference between the direction of that point and the direction of a point which precedes that point by m points, the curve shown in FIG. 2C can be obtained. The curve shown in FIG. 2C can be divided into straight lines and arcs in accordance with the following steps:
(1) Obtaining intervals including distinct nodes, e.g. [L1, R2], [L2, R2], and intervals including clear curves, e.g., [L3, R3]; PA1 (2) Classifying intervals, [A', L1], [R1, L2], ect., other than the intervals obtained by the step (1) into three kinds of intervals including straight lines, curves and unclear lines, and trying to further divide a relatively long interval including curves in the classified intervals into straight lines and curves; PA1 (3) Connecting the adjacent intervals, if possible; and PA1 (4) Determining the positions of the nodes.
The comments of the author of the above-mentioned publication with repect to the above steps will be directly cited from the publication.
"This method is also fairly complicated and it is almost impossible to express it as an equation. It is inherently impossible to perform this division according to the inspiration of a human being by a simple method."
As described by the author of the publication, it is very difficult to generate any contour line and to divide it into straight lines and arcs in a visual recognition apparatus. Further, in order to realize a practical visual recognition apparatus a practical recognition speed must be obtained. To allow the foregoing discriminating to be arithmetically operated by a computer, repetitive and complicated arithmetic operations are in appropriate. In the foregoing method, for instance, in the case where a point proceeds that point by, for example, k points or m points, if the distance between such points is large, any fine change in the curve is averaged and hence cannot be detected. Conversely, if the distance is small, any gentle slight change in the curve is overlooked, or too many concave and convex portions will be undesirably detected due to so-called noises. It is, therefore, necessary to execute many arithmetic operations due to the variety of distances involved and, thereafter, to select a proper one from the results of the arithmetic operations. In addition, since according to the above-mentioned publication, "Intervals are classified into three kinds of intervals including straight lines, curves and unclear lines. An attempt is made to further divide a relatively long interval including curves into curves and straight lines", it is impossible to predict the number of times arithmetic operations will have to be repeated. Thus such a system can be considered an inconvenient system in practical terms. More particularly, in recent years there has been an increasing tendency for dedicated electronic circuit used for arithmetic operations to be designed to reduce the arithmetic operating time and to increase the speed at which the linearity of a line in an image is recognized. However, it is practically impossible to prepare enough electronic circuits to meet the maximum number of times which it can be predicted the relevant arithmetic operations may have to be repeated.